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Record W2914821053 · doi:10.47339/ephj.2018.64

Evaluation of internal temperature of oysters following standard thermal process recipes

2018· article· en· W2914821053 on OpenAlexvenueno aff
Johnson Leung, Environmental Health BCIT School of Health Sciences, Chris Andraza, Lorraine McIntyre, Helen Heacock

Bibliographic record

VenueBCIT Environmental Public Health Journal · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMeat and Animal Product Quality
Canadian institutionsnot available
Fundersnot available
KeywordsOysterFisheryShellfishSteamingEnvironmental scienceFood scienceCooking methodsRaw materialToxicologyFish <Actinopterygii>BiologyEcologyAquatic animal

Abstract

fetched live from OpenAlex

Background &amp; Purpose: The seasonal demand for shellfish such as oysters is on the rise. Shellfish are nutritious foods that may be enjoyed in a variety of ways, from slurping raw oysters to cooking oysters by means of boiling, steaming, pan frying and baking. Most consumers of oysters are aware of potential food safety issues with shellfish. Raw or undercooked shellfish can carry bacteria, viruses and toxins, potentially resulting in foodborne illness. Past outbreaks associated with the consumption of raw and undercooked oysters, prompted the British Columbia Centre for Disease Control (BCCDC) to develop guidelines for those preparing, cooking and consuming shellfish. The recommended cooking temperature and time from the guideline was compared with the temperature and time of standard cooking methods from the Fanny Bay Oyster Market restaurant. The purpose of this project was to determine whether standard cooking methods from restaurants attain the guideline’s recommended 90oC for 90 seconds. Method: Four common cooking methods of Oysters were chosen based on recommendation from Chef Chris Andraza and BCCDC researcher Lorraine McIntyre. Oysters were pan fried, deep fried, baked and grilled. Internal temperatures of cooked oysters were then measured with a probe thermometer. Results for each method were analyzed and compared with the standard of 90oC using the one sample t-test from the statistical software package, NCSS11. Results: One sample t-tests showed statistically differences from the deep fried, baked and grilled methods when compared to the standard of 90oC (p = 0.000). The power for all three methods was 100%, therefore there is confidence that the findings reflect the truth. Experimental temperatures were consistently less than the standard. The pan fried method showed no statistically significant difference when compared to the standard of 90oC (p = 135). The power for pan fried method was 29.2%, therefore there is limited confidence that the findings reflect the truth. Therefore the deep fried, baked and grilled methods required additional cooking time to raise internal temperatures of the oysters. Whereas the pan fried method had achieved the standard but further experimentation is required to eliminate the chance of a type II error. Conclusion: It can be concluded that three out of the four cooking methods (deep fried, baked and grilled) can have significantly different mean temperatures. However, different thermal preparation methods prior to final thermal processing requires consideration to determine cooked oyster consumption safety. One out of the four cooking methods (pan fried) attained the standard temperature 90oC. Therefore, it is recommended for deep fried, baked and grilled cooking methods that the cooking time be extended to achieve an internal temperature of 90oC or higher.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.875
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.075
GPT teacher head0.322
Teacher spread0.247 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2018
Admission routes1
Has abstractyes

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